Prescription stock management system

ABSTRACT

Techniques for automatically tracking, ordering, and replenishing prescription item stock are provided. Based upon a statistical analysis of prescription order transactions, rules may be established to selectively identify which prescription stocked items qualify for automatic stock tracking, ordering, and replenishment. The rules may be based upon metrics such as a daily rate at which each prescription item is dispensed over a specified sampling period as well as the cost of each prescription item. Once qualified, automatic replenishment may be facilitated by calculating stock number minimums and maximums using a statistical analysis of the prescription transaction history for qualifying prescription items. The minimum and maximum stock number values may be used to trigger the generation of purchase orders and to specify how much stock needs to be ordered for each qualifying prescription item as it is replenished.

CROSS REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.15/042,836, filed Feb. 12, 2016, the disclosure of which is incorporatedherein by reference in its entirety.

TECHNICAL FIELD

The present disclosure generally relates to techniques for automaticallytracking, ordering, and replenishing prescription item stock and, moreparticularly, to techniques utilizing a statistical analysis ofprescription order transactions to identify prescription items thatqualify for stock tracking, when to order additional stock, and how muchstock to order.

BACKGROUND

Stock tracking and ordering for prescription drugs differs fromtraditional stock inventory tracking associated with retailers. Some ofthese differences may be attributed to retailer stock beingpromotionally driven and, as a result, somewhat predictable.Furthermore, prescription drugs, if ordered too soon or in too greatamount, risk expiration prior to sale, thereby increasing the cost borneby the pharmacy.

Optimally, prescription stock should be sold prior to expiring but withenough cover on hand in the event that demand outpaces the rate at whichnew stock may be ordered and replenished. However, attempts to do sohave conventionally required a great deal of observation, inventory, andmanual ordering of new prescription drugs on a per-store level. Andbased upon the somewhat unpredictable nature of prescription drug sales,manual ordering may result in an inventory overstock or shortage. Tofurther complicate matters, the rate at which some prescription itemsare dispensed and their cost may greatly differ among stockedprescription items at a single pharmacy. Because it is undesirable torisk overstocking more expensive prescription items, traditional stockordering processes force pharmacies to order new stock more frequentlyfor prescription items for that are more often dispensed and/or have alower cost, which complicates the ordering process.

As a result, automatic stock tracking and ordering is useful butpresents several challenges.

SUMMARY

In an embodiment, a centralized computing device is provided thatfunctions to bridge several networks and/or pharmacy locations together.The centralized computing device may function to aggregate and storeprescription item transactions from several pharmacy locations and makethis data accessible to pharmacy computers at each pharmacy location,other third parties, and/or other computing devices. The one or morecomputing devices may run one or more applications and/or userinterfaces that facilitate the selection of various rule parameters,which may be applied to each prescription item to identify whether aprescription item qualifies for automatic stock tracking, ordering, andreplenishment.

The rule parameters may leverage specific metrics calculated from astatistical analysis of the prescription item transactions for aspecified sampling period, for each prescription item, to determinewhich prescription items qualify for automatic stock tracking, ordering,and replenishment. In an embodiment, the rule parameters may specifyvarious ranges of average daily dispensing frequency values of aprescription item over the sampling period and a range of costs of theprescription, which need to be met for a prescription item to qualifyfor automatic stock tracking, ordering, and replenishment.

Furthermore, once a prescription item qualifies for automatic stocktracking, ordering, and replenishment, embodiments include usingadditional metrics calculated from the prescription item transactions toset a minimum stocked number. The minimum stocked number may act as athreshold that triggers a purchase order being generated once theprescription item stock inventory falls below this number. In addition,the metrics may be used to calculate a maximum stocked number ofprescription items to keep on hand in the pharmacy. Rule parameters mayalso provide for exceptions that may apply to specific pharmacylocations, regions, countries, specific dates, etc., to provideadditional flexibility and to ensure that the appropriate amount ofprescription items are ordered at the right time and in the rightamounts.

BRIEF DESCRIPTION OF THE DRAWINGS

The figures described below depict various aspects of the system andmethods disclosed herein. It should be understood that each figuredepicts an embodiment of a particular aspect of the disclosed system andmethods, and that each of the figures is intended to accord with apossible embodiment thereof. Further, whenever possible, the followingdescription refers to the reference numerals included in the followingfigures, in which features depicted in multiple figures are designatedwith consistent reference numerals.

FIG. 1 illustrates a block diagram of an exemplary prescription itemstock management system 100 in accordance with an exemplary embodimentof the present disclosure;

FIG. 2 illustrates a block diagram of an exemplary external computingdevice 200 in accordance with an exemplary embodiment of the presentdisclosure;

FIG. 3 illustrates an exemplary flow diagram 300 illustrating an overallprescription item dispensing, ordering, and replenishment process inaccordance with an exemplary embodiment of the present disclosure;

FIG. 4A illustrates an exemplary user interface screen 400 to facilitatethe determination of whether a prescription item qualifies for automaticstock tracking in accordance with an exemplary embodiment of the presentdisclosure;

FIG. 4B illustrates an exemplary user interface screen 420 to facilitatethe calculation of a minimum stocked number for a qualifyingprescription item in accordance with an exemplary embodiment of thepresent disclosure;

FIG. 4C illustrates an exemplary user interface screen 440 to facilitatethe calculation of a maximum stocked number for a qualifyingprescription item in accordance with an exemplary embodiment of thepresent disclosure;

FIG. 4D illustrates an exemplary user interface screen 460 to facilitatethe calculation of one or more rule exceptions to apply to one or morequalifying prescription items in accordance with an exemplary embodimentof the present disclosure;

FIG. 5 illustrates an exemplary method 500 in accordance with anexemplary embodiment of the present disclosure; and

FIG. 6 illustrates an exemplary method 600 in accordance with anexemplary embodiment of the present disclosure.

DETAILED DESCRIPTION

The following text sets forth a detailed description of numerousdifferent embodiments. However, it should be understood that thedetailed description is to be construed as exemplary only and does notdescribe every possible embodiment since describing every possibleembodiment would be impractical. One of ordinary skill in the art willrecognize, in light of the teaching and disclosure therein, thatnumerous alternative embodiments could be implemented.

Although the embodiments described throughout the disclosure areexplained in the context of a retail store, other embodiments of thepresent disclosure include non-retail contexts as well. For example, insome embodiments, the actions executed upon identification of one ormore trigger conditions may be related to evaluations or surveys in anon-retail context.

It should be understood that, unless a term is expressly defined in thispatent application using the sentence “As used herein, the term‘_(——————)’ is hereby defined to mean . . . ” or a similar sentence,there is no intent to limit the meaning of that term, either expresslyor by implication, beyond its plain or ordinary meaning, and such termshould not be interpreted to be limited in scope based on any statementmade in any section of this patent application.

Furthermore, the embodiments described herein provide several advantagesof a technical nature in addition to traditional techniques for trackingand ordering prescription item stock. For example, by providing a systemwhereby a statistical analysis of prescription item transactions areused as the basis of when to order additional stock, the efficiency ofthis process is improved over manual methods that do not use this data.This improved efficiency not only results in less labor, but alsoresults in less unnecessary purchase orders being generated. Therefore,the embodiments described herein improve the technical aspects ofexisting technology by reducing bandwidth required to submit additionalpurchase orders and also reduce the overall power consumption oftraditional systems.

In addition, by integrating and aggregating prescription item stocktransactions from a pool of pharmacies, rules may be applied to agreater umbrella of pharmacy locations that would otherwise be possible.As a result of this breadth of rule applications, several stores maypotentially gain the advantages described herein from a single set ofrules. This represents an improvement in data processing and dataorganization from existing technologies that yields a real and tangibleimprovement from the systems in use today that do not provide pharmacydata aggregation and integration.

FIG. 1 illustrates a block diagram of an exemplary prescription itemstock management system 100 in accordance with an exemplary embodimentof the present disclosure. Exemplary prescription item stock managementsystem 100 includes any suitable number ‘M’ of computing devices104.1-104.M, which may be associated with or operated by users102.1-102.M (e.g., a pharmacist and/or a pharmacy technician), one ormore computing devices 105, which may be associated with or operated byuser 103 (e.g., a third party user, warehouse personnel, wholesale storepersonnel, etc.), a communication network 112, and a central hostingservice 114, which may include any suitable number ‘N’ of externalcomputing devices 114.1-114.N.

Generally, exemplary prescription item stock management system 100 mayfacilitate users 102.1-102.M accessing prescription item information forthe various patients that have been prescribed prescription items (e.g.,prescription drugs), entering in the details of when a prescription itemhas been dispensed, and ordering stock to replenish dispensedprescription items.

Furthermore, exemplary prescription item stock management system 100 mayfacilitate user 103 accessing central hosting service 114 and/orotherwise viewing order information that is stored on one or more ofexternal computing devices 114.1-114.N. As will be further discussedbelow, this order information may include, for example, informationrelated to pending orders about to be placed with the third partyassociated with user 103 and computing device 105, prescription stockfiles transmitted from one or more computing devices 104.1-104.M tocentral hosting service 114, details regarding purchase orders manuallytransmitted or otherwise sent to central hosting service 114 via one ormore computing devices 104.1-104.M, etc.

Therefore, computing devices 104.1-104.M and 105 may be implemented asany suitable number and/or type of computing devices configured toprovide a user interface to facilitate user interaction and tocommunicate with central hosting service 114. In an embodiment, each ofcomputing devices 104.1-104.M and 105 may be located in a separatephysical store or location. For example, each of computing devices104.1-104.M may be located or otherwise associated with a separatepharmacy location, while computing device 105 may be located at orotherwise associated with a third party prescription item orderingservice, warehouse, wholesaler, delivery service, etc. In an embodiment,computing devices 104.1-104.M may form a network of pharmacy computers,which may belong to the same pharmacy region (e.g., pharmacy locationswithin a city or within a particular portion of a city), pharmacylocations within a group of regions, pharmacy locations within the samecountry, pharmacy locations within a group of countries or separatecountries, etc.

In various embodiments, computing devices 104.1-104.M and/or computingdevice 105 may be implemented as computer terminals, laptop computers,desktop computers, tablet computers, computer terminals, etc., which maybe configured to allow a respective user (e.g., users 102.1-102.M and/oruser 103) to query and/or update customer information, orderinformation, and/or prescription information stored in central hostingservice 114 (i.e., in one or more external computing devices114.1-114.N). Additionally or alternatively, one or more users102.1-102.M may use a respective computing device 104.1-104.M to enablestore-to-store prescription filling. In an embodiment, one or morecomputing devices 104.1-104.M and/or 105 may provide respective one ormore users 102.1-102.M and/or 103 with secure access to one or moreexternal computing devices 114.1-114.N. For example, computing device104.1 may facilitate secure sign on and/or authentication procedures toallow user 102.1 to access one or more external computing devices114.1-114.N via communication network 112.

Computing devices 104.1-104.M and/or computing device 105 may beconfigured to communicate with central hosting service 114 viacommunication network 112 using any suitable number and/or type ofcommunications protocols in conjunction with any suitable number and/ortype of wired and/or wireless links. For example, one or more computingdevices 104.1-104.M and/or computing device 105 may be coupled tocommunication network 112 via one or more landline, Internet ServiceProvider (ISP) backbone connections, satellite links, public switchedtelephone networks (PSTNs), etc., which may be represented as links101.1-101.M, for example, as shown in FIG. 1.

Communication network 112 may be configured as any suitable networkconfigured to facilitate communications between one or more computingdevices 102.1-102.M, computing device 105, and central hosting service114. For example, communication network 112 may be coupled to one ormore external computing devices 114.1-114.N via one or more landline,Internet Service Provider (ISP) backbone connections, satellite links,public switched telephone networks (PSTNs), etc., which may berepresented as link 101.4, for example, as shown in FIG. 1.

To provide additional examples, communication network 112 may include aproprietary network, a secure public internet, a mobile-based network, avirtual private network, etc. Communication network 112 may include anysuitable number of interconnected network components that form anaggregate network system, such as dedicated access lines, plain ordinarytelephone lines, satellite links, cellular base stations, a publicswitched telephone network (PSTN), etc., or any suitable combinationthereof.

In some embodiments, communication network 112 may facilitate one ormore computing devices 102.1-102.M and/or computing device 105connecting to the Internet. In embodiments in which communicationnetwork 112 facilitates a connection to the Internet, datacommunications may take place over communication network 112 via one ormore suitable Internet communication protocols. In various embodiments,communication network 112 may be implemented, for example, as a wirelesstelephony network (e.g., GSM, CDMA, LTE, etc.), a Wi-Fi network (e.g.,via one or more IEEE 802.11 Standards), a WiMAX network, etc.

Again, central hosting service 114 may include one or more externalcomputing devices 114.1-114.N, which may be implemented as any suitablenumber of components configured to store data, receive data from one ormore computing devices 102.1-102.M and/or computing device 105 (or oneanother), and/or send data to one or more computing devices 102.1-102.Mand/or computing device 105 (or one another) via communication network112 or any other suitable combination of wired and/or wireless links. Invarious embodiments, one or more external computing devices 114.1-114.Nmay be configured to execute one or more applications to facilitate oneor more aspects of the functionality used in accordance with one or moreembodiments as discussed herein.

For example, one or more external computing devices 114.1-114.N may beimplemented as one or more back-end components, which may includecomputing and/or storage devices such as one or more back end servers114.1, one or more database servers 114.2, one or more databases 114.3,and/or one or more external computing devices 114.N. Although FIG. 1illustrates central hosting service 114 as including only four differenttypes of back-end components, it will be appreciated that centralhosting service 114 may include any suitable number and/or type ofback-end components to facilitate the appropriate functions of theembodiments as described herein.

For example, back-end server 114.1 may be implemented as any suitablenumber of web servers configured to provide Internet communications toone or more computing devices 104.1-104.M and/or computing device 105and/or to support one or more applications installed on one or morecomputing devices 104.1-104.M and/or computing device 105.

To provide another example, database server 114.2 may be implemented asany suitable number and/or type of servers that are configured to accessdata from database 114.3, which may store data such as a history ofplaced orders (e.g., via computing device 105), current orders, customerprofile information, prescription item information (e.g., drug types anddosages) associated with each customer profile, stock files from eachpharmacy store, and/or a history of prescription item transactions fromeach pharmacy store.

To provide yet another example, external computing device 114.N may beimplemented as any suitable type of computing devices to facilitate userinteraction with central hosting service 114. In such a case, externalcomputing device 114.N may receive user input defining rule parametersor other communications from user 115. As further discussed below, theserule parameters may form the overall rule processing to facilitateautomatic stock tracking, ordering, and replenishment of dispensedprescription item stock, as further discussed herein. In an embodiment,upon the rule parameters triggering stock replenishment, one or moreexternal computing devices 114.1-114.N may generate a purchase order andtransmit or otherwise communicate the purchase order to a suitable partyfor fulfillment (e.g., to computing device 105).

Furthermore, because one or more computing devices 104.1-104.M maycommunicate with external computing devices 114.1-114.N, users102.1-102.M may view a prescription item's current availability (e.g.,whether a prescription item is in stock or out of stock) and use thisinformation to plan ahead when ordering new stock and/or whenestablishing the various rules to facilitate automated stock tracking,ordering, and replenishment, as further discussed herein. Additionallyor alternatively, the one or more computing devices 104.1-104.M mayallow drugs to de dispensed from each pharmacy location in the event ofa network outage, power failure, etc., and thus may be configured tooperate in an offline mode.

In various embodiments, one or more external computing devices114.1-114.N may store and/or access secure data that is of a private,proprietary, and/or sensitive nature. As a result, various embodimentsof one or more external computing devices 114.1-114.N, communicationnetwork 112, and/or one or more computing devices 104.1-104.M mayimplement appropriate security protocols such as encryption, securelinks, network authentication, firewalls, etc., to appropriately protectand secure such data.

Again, database 114.3 may be configured to store any suitable relevantdata as described in the embodiments presented herein related to theoperation of exemplary prescription item stock management system 100.Such data might include, for example, customer profile information,payment information, customer prescription information, prescriptionitem information such as a prescription drug brand, type, and/or dosage,a time and date when each prescription item was dispensed by eachpharmacy and to which customer, a history of prescribed prescriptionitem transactions, a history of orders placed for additionalprescription items, etc. To provide additional examples, data stored indatabase 114.3 may include stock and/or inventory files or otherinformation, stock keeping units (SKUs), price information, storeinformation such as store locations, store numbers, etc. One or more ofexternal computing devices 114.1-114.N may communicate with database114.3 to store data to and/or read data from database 114.3 as needed tofacilitate the appropriate functions of the embodiments as describedherein.

The various embodiments described herein relate to generating, storing,and analyzing (e.g., via one or more of external computing devices114.1-114.N) prescription item transaction data from one or morepharmacies to facilitate automatic stock tracking, ordering, andreplenishment. The transaction data may include any suitable level ofgranularity based upon the desired inventory accuracy and/or thespecific conditions in which purchase orders should be generated. Forexample, the prescription item transaction data may include not onlywhether a particular prescription was filled, but whether theprescription was completely filled, the number of prescription items(e.g., dosage units, pills, capsules, etc.) that were dispensed, whetherthe prescription order was partially filled (e.g., an “owings” exists)due to the amount of a received order or stock on hand not allowing aprescription order to be completely filled when it is picked up. As willbe further discussed below, any portion of the transaction data may beused to trigger the generation and transmission of a purchase order fora particular pharmacy store, which may be in addition to or instead ofpurchase orders that are generated as a result of the minimum stockednumber of prescription items falling below a threshold number.

Each of the one or more computing devices 104.1-104.M may be located inor otherwise associated with a pharmacy or other retail store thatdispenses prescription items, such as prescription drugs. Therefore,each store may maintain a record of internal physical drug inventory atthat particular pharmacy store, but transmit the store's actual stockfiles (e.g., stocking information, a history of transactions, etc.) tocentral hosting service 114. Thus, once a prescription item stock hasbeen depleted to some minimum threshold stocked number, a purchase ordermay be generated via central hosting service 114 to reorder theprescription item stock, thereby replenishing the prescription itemstock up to a maximum stocked number. As additional prescriptions aredispensed, this process may be repeated for each pharmacy store, therebyensuring that ample prescription item stock is on hand at each pharmacylocation to meet their respective demands.

Embodiments described herein facilitate the tracking of prescriptionitem stock and generating purchase orders to replenish depleted stock.For some types of prescription orders, known as “due date” prescriptionorders, the prescription stock is ordered from the manufacturer or athird party prescription delivery company on a one-for-one basis to bedelivered on an agreed upon date, which is typically delivered close towhen the prescription will be dispensed to the patient, as the deliveryof due date prescriptions may be triggered upon prescriptions beingprocessed and transmitted by a pharmacy location user. Due dateprescription orders typically apply to those that are dispensed topatients with chronic ailments, for example. These types of prescriptionorders lend themselves well to advance ordering practices as there is aregular and consistent demand for such drugs, which allows their stockto be depleted and re-ordered in a somewhat predictable manner.

In contrast to due date prescription orders, due now prescription ordersare those in which a pharmacy needs dispensed from its stock holdingimmediately. For example, a patient may visit their physician, have aprescription submitted and filled by the pharmacy, and then pick up thefilled prescription order all in the same day. Due now prescriptionorders, therefore, tend to vary more in their demand, whichtraditionally requires the pharmacy to examine their stocked inventorymore often to determine when a purchase order should be submitted.

Therefore, embodiments of exemplary prescription item stock managementsystem 100 as described throughout the present disclosure areparticularly well-suited to tracking due now prescription orders. To doso, each pharmacy location may transmit or otherwise communicate itsstocking data to central hosting service 114.

For example, as prescription item orders are received, filled,dispensed, and/or as new orders are placed, one or more users102.1-102.M may enter these details into their respective computingdevices 104.1-104.M through a suitable user interface executed thereon.Additionally or alternatively, the stock files may be automaticallyupdated at central hosting service 114, transmitted to central hostingservice 114, and/or modified at central hosting service 114 based uponvarious actions taken by one or more users 102.1-102.M. For example, thestock file stored at central hosting service 114 may automatically beadjusted when a user completes prescription data entry, when aprescription item transaction (e.g., payment) is processed, etc. One ormore users 102.1-102.M may also subsequently manually adjust the stockfiles stored via central hosting service 114 via their respectivecomputing devices 104.1-104.M, for example, to account for variousinconsistencies, damaged items, when a prescription item has expired andneeds to be disposed, etc.

In any event, each pharmacy may transmit their stock file data tocentral hosting service 114. The stock file may indicate various detailsof the history of dispensed prescription items and their currentin-store prescription item inventory. This stock file may be stored, forexample, on one or more external computing devices 114.1-114.N, whereone or more computing devices 104.1-104.M may access the stock filedata. In an embodiment, one or more external computing devices114.1-114.N may store the stock files for an aggregation of any suitablenumber of pharmacies. Furthermore, embodiments include one or moreexternal computing devices 114.1-114.N generating one or more rules,which may be specified based upon various metrics obtained via ananalysis of any number of the transmitted pharmacy stock files. Asdiscussed in further detail below, the rules may be based upon thehistory, cost, and frequency of dispensed prescription items at aparticular pharmacy or a group of pharmacies. These rules may determine,for example, which prescription items qualify for automatic stocktracking and replenishment, a minimum and maximum stocked number tomaintain on hand for each prescription item dispensed by a pharmacy,external factors that may override or adjust these rules, etc.

In an embodiment, the rules generated for each prescription item stockedat one or more pharmacy locations may be used to trigger the generationof a purchase order via central hosting service 114. The rules mayspecify when the purchase order should be generated via central hostingservice 114 (e.g., when a prescription item stock falls below acalculated minimum stocked number) as well as how much prescription itemstock to order (e.g., to bring the in house stock up to the maximumstocked number). These purchase orders may be generated via centralhosting service 114 and sent to the manufacturer, delivery service,warehouse, or other third party (e.g. computing device 105) inaccordance with any suitable techniques.

For example, one or more of external computing devices 114.1-114.N maygenerate an electronic purchase order that is transmitted to a deliveryservice (e.g. computing device 105) in the form of an electronicmessage, notifying the delivery service of the details of theprescription item order. To provide another example, one or more ofexternal computing devices 114.1-114.N may generate and transmit afacsimile to the appropriate party (e.g. computing device 105) with thedetails of the prescription item order, generate and place an automatedphone call (e.g., to user 103), generate and send an automated mailing,receive a notification to place an order, etc. To provide anotherexample, user 115 (e.g., a support office control) may manually generateand/or place purchase orders using any suitable means of communication,such as electronic message transmission, phone calls, facsimile, etc.

FIG. 2 illustrates a block diagram of an exemplary external computingdevice 200 in accordance with an exemplary embodiment of the presentdisclosure. In an embodiment, external computing device 200 may be animplementation of one or more external computing devices 114.1-114.N,for example, as shown in FIG. 2. External computing device 200 mayinclude a processor 202, a communication unit 204, a display 206, a userinterface 208, and a memory 210. Although the embodiments are describedherein as functioning on a single external computing device 200 forsimplicity, embodiments also include the execution of various logicallayers, the use of processing resources, memory, the execution ofapplication data, etc., that is distributed among any suitable number ofexternal computing devices 114.1-114.N that constitute central hostingservice 114.

Processor 202 may be implemented as any suitable type and/or number ofprocessors, such as a host processor for the relevant device in whichexternal computing device 200 is implemented, for example. Processor 202may be configured to communicate with one or more of communication unit204, display 206, user interface 208, and/or memory 210 to send data toand/or receive data from these components.

Communication unit 204 may be configured to enable data communicationsbetween external computing device 200 and one or more other devices,such as one or more computing devices 104.1-104.M, for example, as shownin FIG. 1. In an embodiment, communication unit 204 may be configured toreceive data, such as prescription item transaction data, stockinformation, stock files, etc., from one or more computing devices. Inan embodiment, external computing device 200 may be configured to senddata, including stock file information received from another computingdevice, for example, to another computing device, such as one or morecomputing devices 104.1-104.M and/or one or more external computingdevices 114.1-114.N, as shown in FIG. 1.

Communication unit 204 may be implemented with any combination ofsuitable hardware and/or software to enable these functions. Forexample, communication unit 204 may be implemented with any suitablenumber of wired and/or wireless transceivers, network interfaces,physical layers (PHY), ports, antennas, etc. In embodiments in whichcommunication device 204 is an external computing device, communicationunit 204 may enable communications between other external computingdevices (e.g., one or more of external computing devices 114.1-114.N, asshown in FIG. 1), one or more networks (e.g., communication network 112,as shown in FIG. 1) and/or one or more pharmacy computing devices (e.g.,one or more of computing devices 104.1-104.M, as shown in FIG. 1).

Display 206 may be implemented as any suitable type of display and mayfacilitate user interaction with external computing device 200 inconjunction with user interface 208. For example, display 206 may beimplemented as a capacitive touch screen display, a resistive touchscreen display, etc. In various embodiments, display 206 may beconfigured to work in conjunction with processor 202 and/orcommunication unit 204 to display purchase orders for prescriptionitems, to display details associated with prescription stock files, etc.

User interface 208 may be configured to allow a user to interact withexternal computing device 200. For example, user interface 208 mayinclude a user-input device such as an interactive portion of display206 (e.g., a “soft” keyboard displayed on display 206), an externalhardware keyboard configured to communicate with external computingdevice 200 via a wired or a wireless connection, one or more keyboards,keypads, an external mouse, or any other suitable user-input device.

In embodiments in which external computing device 200 is implemented aspart of a device that performs automated tasks and/or does not otherwiserequire user input (e.g., a web server or other type of server), display206 and/or user interface 208 may not be needed and thus may be omitted.

When communicating with memory 210, processor 202 may be configured tostore to and/or read data from memory 210. In some aspects, processor202 may be configured to communicate with additional data storagemechanisms that are not shown in FIG. 2 for purposes of brevity (e.g.,one or more hard disk drives, optical storage drives, solid statestorage devices, databases, etc.) that reside within, are associatedwith external computing device 200, and/or are accessible viacommunication unit 204.

In accordance with various embodiments, memory 210 may be acomputer-readable non-transitory storage device that may include anycombination of volatile (e.g., a random access memory (RAM), or anon-volatile memory (e.g., battery-backed RAM, FLASH, etc.)). Memory 210may be configured to store instructions executable on processor 202.These instructions may include machine readable instructions that, whenexecuted by processor 202, cause processor 202 to perform various acts.

Memory 210 may include a stock management application 212 and one ormore memory modules utilized by stock management application 212 such asa prescription data aggregation module 213, a qualifying rulecalculation module 215, a minimum stock rule calculation module 217, amaximum stock rule calculation module 219, and an exception rulecalculation module 221. Stock management application 212 may, whenexecuted by processor 202, work in conjunction with one or more of thesemodules, communication unit 204, display 206, and/or user interface 208to perform one or more functions of the aspects as described herein.

Stock management application 212 may include instructions that, whenexecuted by processor 202, facilitate the implementation of a web-basedand/or network-based application platform. This application platform maybe utilized, for example, in conjunction with a retailer and/or pharmacyinfrastructure to support interactions between one or more pharmacycomputing devices (e.g., one or more computing devices 104.1-104.M)and/or one or more other external computing devices (e.g., one or moreexternal computing devices 114.1-114.N). This application platform mayalso be configured to apply rule parameters selected by a user at apharmacy location to specific prescription items prescribed at thatpharmacy location, which may be based on, for example, an analysis ofprescription item transactions for the same pharmacy location or anaggregation of several pharmacy locations. The rule parameters mayprovide the framework for various rules that may specify, for example,which prescription items qualify for automatic stock tracking, ordering,and replenishment, and the minimum and maximum stocked numbersassociated with qualifying prescription items. The selection,application, and implementation of these rule parameters are furtherdiscussed below with reference to FIGS. 4A-4D.

Prescription data aggregation module 213 is a portion of memory 206configured to store instructions, that when executed by processor 202,cause processor 202 to receive prescription transaction data from one ormore pharmacy computers, to associate these prescription itemtransactions with a particular store's file, and to update the store'sstock file. For example, referring back to FIG. 1, user 102.1 mayinteract with computing device 104.1 to manually update prescriptionitem inventory. To provide another example, computing device 104.1 mayperform various stock-updating automated procedures that result inupdates to the stock file for the pharmacy associated with computingdevice 104.1. In either case, embodiments include processor 202executing instructions stored in prescription data aggregation module213 to receive the updated data, to associate the updated data with aparticular pharmacy or store (e.g., a store number) and to update thestock file for the store associated with the updated data.

Again, external computing device 200 may store one or more stock fileslocally (e.g., in a suitable portion of memory 206) or on one or moreexternal computing devices such as external computing devices114.1-114.N. Embodiments include processor 202 executing instructionsstored in prescription data aggregation module 213 to update the data atany of these locations where the stock files may be stored.

In an embodiment, processor 202 may execute instructions stored inprescription data aggregation module 213 to organize stock files and/orprescription item transactions in any suitable manner such that the datamay be provided to users via each pharmacy location's respectivecomputing device. Referring back to FIG. 1 as an example, user 115(e.g., a support office control) may interact with one or more externalcomputing devices 114.1-114.N to specify various rule parameters forprescription items stocked by that particular pharmacy. To do so, one ormore external computing devices 114.1-114.N may need to accessprescription item transactions over a specified sampling period (e.g.,the last month, 6 months, a year, etc.). Thus, embodiments includeprocessor 202 executing instructions stored in prescription dataaggregation module 213 to not only aggregate and store the prescriptionitem transactional data and/or stock files from several prescriptionstores, but to format this data and/or make this data available to oneor more other external computing devices 114.1-114.N, such that rulesmay be generated using this data to facilitate automatic stock tracking,ordering, and replenishment.

Qualifying rule calculation module 215 is a portion of memory 206configured to store instructions, that when executed by processor 202,cause processor 202 to identify various conditions that, upon beingsatisfied, result in a prescription item qualifying for automatic stocktracking, ordering, and replenishment. In an embodiment, processor 202may execute instructions stored in qualifying rule calculation module215 to generate rules that may be applied to each prescription item in apharmacy's inventory using the history of prescription itemtransactions.

For example, a pharmacy may maintain stock for several prescriptionitems, but only choose to track and automatically replenish a subset ofthose prescription items. Although daily dispensing frequencies may varythroughout a sampling period, various statistical analyses may beapplied to the prescribed prescription item transactions to derivevarious metrics in an attempt to forecast future demand, set theappropriate triggers to order additional prescription item stock, and/orset a minimum and a maximum stocked number to guide the orderingprocess.

An example of a parameter used in the formulation of a rule may includea range of one or more metrics that may derived from a statisticalanalysis of prescription item transactions, such as average dailydispensing frequency values over a sampling period, for example. Thesampling period may be specified by a user or be a default samplingperiod, which is further discussed below with reference to FIGS. 4A-4D.That is, it is desirable for a pharmacy to automatically track, order,and replenish stock for prescription items that are dispensed at ahigher average daily frequency compared to other prescription items, asdoing so creates less risk of prescription items being of overstocked.

Another example of a parameter used in the formulation of a rule mayinclude a range of costs of prescribed items. It is more desirable for apharmacy to automatically track and replenish stock for prescriptionitems that are cheaper because, if extra stock is ordered and needs tobe disposed, the pharmacy absorbs less of a financial burden in doingso. Embodiments include processor 202 executing instructions stored inqualifying rule calculation module 215 to facilitate a user specifyingany suitable range, combination, and/or weighting of various parametersto determine which stocked items may qualify for automatic stocktracking and replenishment. The generation and application of qualifyingrules are further discussed below with reference to FIG. 4A.

Minimum stock rule calculation module 217 is a portion of memory 206configured to store instructions, that when executed by processor 202,cause processor 202 to calculate a rule for the minimum stocked numberto maintain on hand for a particular qualifying prescription item. Inother words, once a prescription item qualifies for automated stocktracking, ordering, and replenishment, as discussed above with referenceto qualifying rule calculation module 215, a user may further specify,based upon various parameters calculated from a statistical analysis ofthat prescribed prescription item's transactions, the minimum stockednumber to maintain on hand for that prescription item. In someembodiments, the minimum stocked number may act as a trigger, forexample, upon which to generate and transmit a purchase order, such thatonce the prescription item's stock falls below the minimum number, thepurchase order is automatically, semi-automatically, or manuallygenerated.

But in other embodiments, it may be desirable to “overstock” certainprescription items, based upon demand, for example. In embodiments inwhich a prescription drug item is overstocked, execution of minimumstock rule calculation module 217 via processor 202 may compensate forany overstock by reducing the minimum stocked number such that stockordering is deferred to reduce the overstock. Thus, embodiments includethe calculation of an adjusted minimum stocked number based upon aparticular prescription item being overstocked by reducing the minimumstocked number that would otherwise be applicable if the prescriptionitem was not overstocked. The adjusted minimum stocked number may becalculated, for example, based upon a proportion of the overstock, theamount of overstock, etc.

Again, the average daily dispensing frequency value of a prescribed itemmay be used as part of the determination of whether particularprescribed items qualify for automatic stock tracking, ordering, andreplenishment. In addition, the average daily dispensing frequency value(or a multiple thereof) may likewise be used to calculate the minimumstocked number. That is, if the sampling period is 30 days, the averagedaily dispensing frequency value would be calculated by dividing thetotal prescriptions dispensed over the 30 day interval for a particularqualifying prescription item by 30. The average daily dispensingfrequency value or a multiple thereof (2 times this number would yieldthe anticipated number of prescriptions to be dispensed over two days inthe sampling period) may be used to calculate the minimum stockednumber.

To provide another example, a maximum average daily dispensing frequencyvalue over the sampling period may be calculated and used as the basisfor calculating the minimum stocked number. For example, if the samplingperiod is 30 days, a user may specify that only a subset of the totalprescriptions dispensed over the 30 day interval should be averaged asopposed to the entire sampling period. In other words, if a userspecifies that the 10 highest daily dispensing frequency values withinthe 30 day sampling period are to be used, processor 202 may calculatethe maximum average daily dispensing frequency value by summing thetotal prescriptions dispensed over the ten days and dividing this numberby 10.

To provide an illustrative example of a maximum average daily dispensingfrequency value calculation, dispensing frequency values over an 11 dayperiod may include the following values: 10, 10, 10, 10, 17, 17, 17, 17,20, 20, and 20. Selecting the top ‘x’ highest daily dispensingfrequencies, whereby x=4, specifies the 4 highest daily dispensingfrequency values, thereby selecting values of 20, 20, 20, and 17 fromthe 11 day sampling period, and averaging these would yield a maximumaverage daily dispensing frequency value of 19.25. In the event that auser specifies a number ‘x’ of the highest daily dispensing frequencyvalues that exceeds the available number of daily dispensing frequencyvalues, embodiments include the maximum average daily dispensingfrequency value calculation being performed by iteratively reducing x by1 until the calculation can be made. Using the previous example, if auser specified x=12, because only 11 days of frequency values areavailable based upon the sampling period that has been selected,embodiments include x being instead set to 11 (and then 10, 9, 8, etc.,as needed based upon the sampling period) until x is equal to at leastthe same number of days in the selected sampling period (in this case11), to calculate the maximum average daily dispensing frequency value.

To provide another example, a maximum daily dispensing frequency valuemay be calculated and used as the basis for calculating the minimumstocked number, which may utilize the same or similar dispensingfrequency values over a specified period as part of the calculation. Forexample, a user may specify a number of ‘x’ occurrences within thesampling period to be averaged (e.g., a number of daily dispensingfrequency values, such as 4), a tolerance from which these same valuesmay deviate from one another (e.g., 10%), and a sampling period overwhich to analyze dispensing frequency values (e.g., 30 days). Tocalculate the maximum daily dispensing frequency value, embodimentsinclude processor 202 finding the four top daily dispensing frequencyvalues within the month that are within 10% of one another. Once thesefour daily dispensing frequency values are identified, processor 202 maycalculate the maximum daily dispensing frequency value by averagingthem.

To provide an illustrative example, embodiments include processor 202first reducing the number of occurrences to be considered using theappropriate tolerance and then applying the specified logic to match thenumber of occurrences. Thus, for ‘x’=4, a tolerance=10%, and values of51, 52, 53, and 97, the number of occurrences would be reduced to 3,because only three values exist within the 10% tolerance of one another(51, 52, and 53), and therefore the selected values would be 51, 52, and53. Continuing this example, calculating the maximum daily dispensingfrequency value from these three values would result in a maximum dailydispensing frequency value of 52.

In an embodiment, the maximum daily dispensing frequency value may becalculated in an iterative manner such that the data is analyzed until anumber of occurrences is found (either an exact match or within thespecified tolerance). To provide another illustrative example, if x=5,the specified tolerance=15%, and the daily dispensing frequency valuesare 100 and 224, then the number of occurrences is 1 and the selectedvalue is 224, because there are no occurrences within 15% of each other.

To provide yet another illustrative example of a maximum dailydispensing frequency value calculation, if x=4, the tolerance=15%, andthe values are 10, 10, 10, 10, 17, 17, 17, 17, 20, 20, and 20, then thenumber of occurrences should be 4 and the selected values should be 20,20, 20, 17, resulting in the maximum daily dispensing frequency value of(20+20+20+17)/4=19.25.

Embodiments include processor 202 executing instructions stored inminimum stock rule calculation module 217 to facilitate a userspecifying any suitable number and/or type of rule parameters upon whichto calculate of the minimum stocked number. For example, a user mayspecify rule parameters that calculate the minimum stocked number as thegreater of any combination of (1) the average daily dispensing frequencyvalue over a sampling period (or a multiple thereof), (2) a maximumaverage daily dispensing frequency value, and/or (3) the maximum dailydispensing frequency value. The generation and application of rules thatspecify the minimum stocked number of a qualifying prescription item tokeep on hand before ordering more are further discussed below withreference to FIG. 4B.

Maximum stock rule calculation module 219 is a portion of memory 206configured to store instructions, that when executed by processor 202,cause processor 202 to calculate a maximum stocked number to maintain onhand for a qualifying prescription item. This maximum stocked number maybe used, for example, as a guide when the purchase order is generatedand transmitted to replenish depleted stock. For example, the purchaseorder may order an amount of prescription item stock that is thedifference between the minimum stocked number (or less if, whengenerated, there is less than the minimum stocked number available) andthe maximum stocked number.

In various embodiments, processor 202 may calculate the maximum stockednumber using any suitable number and/or type of metrics derived from theanalysis of the prescribed prescription item transactions, such as anyof those discussed above that are used to calculate the minimum stockednumber, for example.

For example, a number of days of stock cover may be calculated basedupon a multiple of the average daily dispensing frequency value over aspecified sampling period, which may be the same average dailydispensing frequency value that is used in the calculation of theminimum stocked number. To provide an illustrative example, if 2 days ofstock cover are used as the basis of the maximum stocked numbercalculation, then the maximum stocked number may be calculated bymultiplying the average day quantity by the number of days stock cover,then adding the minimum stock value, as shown in Eqn. 1 below:Maximum Stocked Number=[(Average daily dispensing frequency value×2)+theminimum stocked number].  Eqn. 1:

The generation and application of rules that specify the maximum stockednumber of a qualifying prescription item to keep on hand are furtherdiscussed below with reference to FIG. 4C.

Exception rule calculation module 221 may be a portion of memory 206configured to store instructions, that when executed by processor 202,cause processor 202 to apply various user-specified rule parameters,which may be applied to the aforementioned qualifying rules or used toadditionally or alternatively specify conditions that result in an orderbeing placed, regardless of whether a particular stocked prescriptionitem qualifies for automatic stock tracking, ordering, andreplenishment. Furthermore, the various user-specified rule parametersmay be applied to the minimum stocked calculation rules and/or maximumstocked calculation rules to provide for greater flexibility. Forexample, a user may specify various factors that are applied to theaforementioned rules to customize their respective outcomes. Thesefactors may take into account a specific pharmacy, a particular region,specific dates in which it may be inaccurate to completely rely on theforecasting resulting from the analysis of prescribed item transactions,etc. The generation and application of these factors are furtherdiscussed below with reference to FIG. 4D.

To provide another example, embodiments include other types ofprescription order events resulting in the generation of a purchaseorder to replenish inventory regardless of whether that particularprescription items qualifies for stock tracking. That is, the demand forprescription item inventory may be driven by both prescribed items thatare dispensed as well as prescription item orders that are received. Toprovide an illustrative example, in some instances a partialprescription fill or an owings may be created when on hand prescriptionitem stock is not sufficient to completely fill a prescription order.Therefore, embodiments include the prescription transaction data that isreceived by external computing device 200 including an indication of anysuch partial fillings and how much of the prescription item was able tobe dispensed.

Instructions in exception rule calculation module 221 may allow a userto specify rule parameters such that that purchase orders are generatedand transmitted upon detecting any such partial filings, resulting inthe prescription items having an higher demand (which caused the partialfilling to occur) to be restocked regardless of whether the prescriptionitem otherwise qualifies for automatic stock tracking and replenishment.However, in the event that a partially filled prescription item doesqualify for automatic stock tracking and replenishment, embodimentsinclude exception rule calculation module 221 allowing a user to specifyrule parameters that act as an override when partial fillings aredetected, causing processor 202 to generate a purchase order as soon thepartial filling is detected even if the stocked number for aprescription item qualifying for automatic stock tracking andreplenishment has not yet been depleted below the minimum stocked numberthreshold.

Because external computing device 200 may receive and store prescriptionitem transactions for any suitable number of pharmacies, the statisticalanalysis of a prescribed prescription item's transactions may beperformed over any suitable number of pharmacies, regions, countries,etc. For example, rules may use metrics calculated from an analysis ofprescribed prescription item's associated with a single pharmacy orseveral pharmacies, although the rules may be applied to thetransactional data that is associated with prescription item stock at aparticular pharmacy location.

In this way, embodiments allow for errors introduced from small samplesof prescribed item transactional data to be reduced or eliminated, whileproviding a user with the flexibility of customizing rule parametersutilizing prescribed prescription item transaction data for a singlestore if the data is sufficiently accurate.

FIG. 3 illustrates an exemplary flow diagram 300 illustrating an overallprescription item dispensing, ordering, and replenishment process inaccordance with an exemplary embodiment of the present disclosure. Flowdiagram 300 represents a timeline of the total stocked number of aparticular prescription item at various times 302, 304, 306, and 308.

As shown in FIG. 3, time 302 is associated with a time just after newstock is acquired, as the height of the bar at time 302 is equal to themaximum stocked number, which may be calculated for the prescriptionitem as discussed above.

At time 304, some of the prescription item has been dispensed, therebyreducing the overall stocked number from time 302, as shown by thereduced height of the bar at time 304. However, at time 306, thedispensing of the prescription item continues until the stocked numberis below the minimum stocked number for the prescription item, whichagain may be calculated in the various manners discussed above. As aresult, a purchase order may be generated and transmitted at time 306,resulting in the prescription item stock being replenished at time 308by an amount equal to the maximum stocked number upon receiving deliveryof the prescription item. This process may repeat over any number ofcycles using the minimum and maximum stock number rules as discussedabove and elsewhere herein.

Furthermore, because the sampling period specified by each of theaforementioned qualifying rule, minimum stocked number calculation rule,and maximum stocked number rule may be based upon recent samplingperiods, the results of the rules being applied to various prescriptionitems may vary over time. For example, a prescription item thatqualifies for automatic stock tracking and replenishment using one monthof prescribed prescription item transaction data may not do so the nextmonth if the conditions specified by the rule are not met the followingmonth. Similarly, a prescription item that does not qualify forautomatic stock tracking and replenishment using one month of prescribedprescription item transaction data may qualify the next month if theconditions specified by the rule are met the following month.

Additionally, the minimum and maximum stock number calculations for aqualifying prescription item may dynamically update over time using theresulting metrics from an analysis of the most recent prescription itemtransaction data. In this way, embodiments of the automatic stocktracking, ordering, and replenishment system dynamically adapt toaccurately anticipate and forecast future demand based upon recentchanges in a prescribed item's dispensed rate.

FIG. 4A illustrates an exemplary user interface screen 400 to facilitatethe determination of whether a prescription item qualifies for automaticstock tracking in accordance with an exemplary embodiment of the presentdisclosure. In an embodiment, exemplary user interface screen 400 is anexample of what may be displayed on a suitable computing device that isconfigured to communicate with one or more in-house pharmacy computers.For example, exemplary user interface screen 400 may be displayed on oneor more external computing devices 114.1-114.N, as shown in FIG. 1. Insuch a case, the various rule parameters, which are further discussedbelow, may be input by an appropriate user, such as user 115, forexample, via user interaction with one or more one or more externalcomputing devices 114.1-114.N.

In an embodiment, the various user inputs and rule parameters asdiscussed herein with reference to FIGS. 4A-4D may be communicated froman in-house pharmacy computing device to one or more back-end and/orexternal computing devices, such as external computing devices114.1-114.N, for example, as shown in FIG. 1. In an embodiment, theapplication shown throughout FIGS. 4A-4D may be supported via processor202 executing one or more instructions and/or modules stored in memory210, such as the execution of stock management application 212, forexample, as shown in FIG. 2. Furthermore, embodiments include theoverall rule parameters, which specify how the resulting decisions foreach rule are determined, being stored on the one or more back-endand/or external computing devices while allowing users to access andview this data via their respective in-house pharmacy computers.

As shown in FIG. 4A, exemplary user interface 400 includes a tabbed gridlayout with tabs 402, 404, 406, and 408. As shown in FIG. 4A, exemplaryuser interface 400 corresponds to a view that is displayed upon a userselecting tab 402, which allows a user to specify various ruleparameters. In this case, the rule parameters result in a determinationof which prescribed items qualify for automatic stock tracking,ordering, and replenishment.

Exemplary user interface 400 also includes several interactive portionsas well as other portions that provide feedback to the user, such as agrid association interactive button 409, a grid code field 410, a gridstructure interactive button 411, a grid name interactive field 412, aninteractive cell options field 413, a number of stores field 414, a grid415, an interactive comments field 416, an interactive grid descriptionfield 418, and an update comments field 419.

As will be further discussed below with reference to FIGS. 4B-4D, someportions of exemplary user interface 400 may remain the same as a userselects different tabs 402, 404, 406, and 408, while other portions ofexemplary user interface 400 may change to facilitate additional oralternate functions.

The grid shown in FIG. 4A is applicable to the prescription itemtransactions for a single store over a specified sampling period.However, a user may specify any suitable number of stores by selectinggrid association interactive button 409, which may prompt a user toselect specific stores to associate with the grid rules. Upon selectinga number of stores for which the grid rule applies, the selection may bedisplayed as feedback in the number of stores field 414. In anembodiment, the grids shown in FIGS. 4A-4D may function as a single“global” grid for a number of pharmacy stores, such as all stored overwhich stock data is collected, for example.

A user may also name the rule via grid name interactive field 412 andadd comments in interactive comments field 416, as shown in FIG. 4A.Upon a user adding comments to interactive comments field 416, thesecomments may be indicated in the updated comments field 419 when therule is later accessed or otherwise subsequently opened.

As further discussed below, the various parameters used for the ruleshown in FIG. 4A may utilize prescription item transaction data for oneor more selected pharmacies or stores. The prescription item transactiondata may be based upon any suitable sampling time period, such as thelast 30 days of transactions, for example. In some embodiments, thissampling period may be a predetermined or default period. But in otherembodiments, this sampling period may be specified by a user, forexample.

Embodiments include users generating different rules for each differentpharmacy or store, which may each include different parameters, samplingperiods, and/or different store selections. In accordance with suchembodiments, users may uniquely name their rules in any suitable manner,which may be identified by grid code field 410, for example. As usersupdate their rules to include different stores, different samplingperiods, and/or to specify different parameters, users may maintain alog of tracked changes using interactive grid description field 418. Bysaving user comments with each rule, different users may adjust the samerule that is used for a single pharmacy location in a manner thatconveys the types of changes and when these changes were made to otherusers as each rule is accessed.

Again, exemplary user interface 400 includes a grid 415, which may be ofany suitable size. As shown in FIG. 4A, grid 415 has a vertical axislabeled “daily frequency scripts,” and a horizontal axis labeled“ranging cost.” In this example, the rule parameters are the result ofthe intersection of the ranges defined by the vertical axis grid cellsand the horizontal axis grid cells, which represent average dailyfrequency prescriptions and cost, respectively. However, any suitabletype of metrics may be used to define the rule parameters such that adetermination may be accurately made regarding which of the prescriptionitems qualifies for automatic stock tracking, ordering, andreplenishment.

Using the example shown in FIG. 4A, the vertical axis indicates a numberdaily frequency prescriptions, or average daily dispensing frequencyvalues, that increase from zero per day to some maximum number, which isshown in FIG. 4A as “9999,” but may be any suitable frequency value. Forexample, a pharmacy may dispense several products over a sampling periodat different numbers per day, resulting in each prescribed item fallinginto one of the ranges as indicated by the tick marks on the verticalaxis of grid 415. In an embodiment, a user may adjust these tick marks,and thus the ranges of each average daily dispensing frequency valueassociated with the vertical axis of grid 415. For example, a user mayselect grid structure interactive button 411 to specify the minimumaverage daily dispensing frequency value, the maximum average dailydispensing frequency value, the number of vertical grid cells, and/orthe ranges associated with each of the vertical grid cells. In this way,a user may tailor the grid based upon a store's specific prescriptionitem transactions to vary the granularity of ranges as desired.

Continuing to reference FIG. 4B, the horizontal axis indicates a costthat increases from zero to some maximum number, which is shown in FIG.4A as “9999” but may be any suitable cost value. For example, a pharmacymay dispense several products over a sampling period that have differentcosts, resulting in each prescribed item falling into one of the rangesas indicated by the tick marks on the horizontal axis of grid 415. In anembodiment, a user may adjust these tick marks, and thus the ranges ofcosts associated with the horizontal axis of grid 415. For example, auser may select grid structure interactive button 411 to specify theminimum cost, the maximum cost, the number of horizontal grid cells,and/or the ranges associated with each of the horizontal grid cells,thereby providing additional customization based upon a store's specificprescription item transactions.

In various embodiments, any suitable cost metric may be used thatadequately conveys the need to automatically track, order, and replenishstock of a particular prescription item For example, the cost may be thecost of a prescribed unit of a particular prescription drug (e.g., asingle dosage) a prepackaged unit of several doses, a minimum packagednumber of doses, a number of packs, an optimum and/or preferred packsize, etc. Embodiments also include a user specifying the type of cost,the type of currency used, etc. In this way, embodiments allow the stocktracking and replenishment techniques discussed herein to be applicableregardless of local currency and/or customs.

To define which prescription items qualify for automatic stock tracking,ordering, and replenishment, a user may utilize interactive cell optionsfield 413 to apply the rule for prescription items that fall within theranges defined by particular grid cells within grid 415. For example, auser may select grid cell 415.1 and specify this cell option as “no”using interactive cell options field 413. As a result, prescriptionitems that are dispensed at an average daily dispensing frequency above72 per day, and also have a cost above $200 per unit, will not qualifyfor automatic stock tracking and replenishment. Similarly, a user mayselect grid cell 415.2 to specify that prescription items that aredispensed at an average daily dispensing frequency below 2 per day, andalso have a cost below $0.50 per unit, will not qualify for automaticstock tracking, ordering, and replenishment.

To provide additional examples, a user may select grid cell 415.3 tospecify that prescription items that are dispensed at an average dailydispensing frequency between 28 and 72 per day, and also have a costbetween $20-$50 per unit, will qualify for automatic stock tracking,ordering, and replenishment. Furthermore, a user may select grid cell415.4 to specify that prescription items that are dispensed at anaverage daily dispensing frequency above 72 per day, and also have acost less than $0.50 per unit, will qualify for automatic stocktracking, ordering, and replenishment. Finally, a user may select gridcell 415.5 to specify that prescription items that are dispensed at anaverage daily dispensing frequency between 28 and 72 per day, and alsohave a cost less than $0.50 per unit, will qualify for automatic stocktracking, ordering, and replenishment.

A user may repeat this process to assign “yes,” “no,” or “excluded”status to each grid cell within grid 415. While the assignment of yesand no to specific grid cells may represent whether stock tracking andreplenishment is performed for stocked prescription items meeting eachrespective cell's frequency and cost ranges, a cell may be set to“exclude” to specify that automatic stock tracking and replenishmentcalculations are not required for a period of time for prescriptionstock items associated with a respective cell's frequency and costranges, and the daily frequency ranging values will not be re-calculatedduring the next elaboration; previously calculated values will beconsidered instead.

In this way, a complete set of rule parameters is established for anentire pharmacy's stock. Once the rule is established, any prescriptionitems in stock meeting the average daily dispensing frequency value andcost ranges will qualify for automatic stock tracking, ordering, andreplenishment. The user interface may then be further utilized tospecify, for those prescription items that do qualify for automaticstock tracking, ordering, and replenishment, additional parameters tospecify the minimum stock number that triggers a purchase order beinggenerated and transmitted to replenish the depleted stock. This isfurther discussed below with reference to FIG. 4B.

FIG. 4B illustrates an exemplary user interface screen 420 to facilitatethe calculation of a minimum stocked number for a qualifyingprescription item in accordance with an exemplary embodiment of thepresent disclosure. In an embodiment, exemplary user interface screen420 corresponds to a transition from another exemplary user interfacescreen 400, 440, or 460 due to a user selecting tab 404 while in theother exemplary user interface screen. As discussed above, exemplaryuser interface 420 shares several portions with other exemplary userinterfaces. For example, grid association interactive button 409, gridcode field 410, grid structure interactive button 411, grid nameinteractive field 412, number of stores field 414, interactive commentsfield 416, interactive grid description field 418, and update commentsfield 419 are also displayed in exemplary user interface 420. Theseportions may perform the same functions as discussed above withreference to FIG. 4A.

However, exemplary user interface 420 also includes an interactive celloptions field 422, which a user may be utilized to set the various ruleparameters for each prescription item in grid 415 that qualifies forautomatic stock tracking and replenishment. For example, referring backto FIG. 4A, exemplary user interface 400 included grid 415, whichindicated the ranges of metrics for various prescription items that,when met, would qualify those prescription items for automatic stocktracking, ordering, and replenishment.

These same qualifying grid cells are shown in grid 415, as shown in FIG.4B. That is, grid cells 415.1 and 415.2 are now labeled “not stocked,”while grid cells 415.3-415.5 have a selected minimum stock calculationrule applied to these cells. Any suitable metrics based upon an analysisof prescription item transaction data may be used for the calculation ofthe minimum stocked number, and are not limited to the examplesdiscussed herein.

For example, interactive cell options field 422 provides a user with theoption to select one of the grid cells within grid 415 and to identifythat grid cell as either “stocked” or “not stocked.” In an embodiment,grid cells that do not qualify for automatic stock tracking andreplenishment may be set to “not stocked” by default. Upon selecting thestocked option, a user may select one or more ways in which the minimumstocked number for the prescription item is calculated and selectinteractive “ok” button 424 to apply these selections to an individualgrid cell. In an embodiment, two or more options may be selected, withthe greater number of these calculations yielding the minimum stockednumber for the particular prescription items that fall within the rangesdefined by each of the grid cells within grid 415.

For example, a user may define the minimum stocked number as a number ofprescription items dispensed over a number of at a rate of the averagedaily dispensing frequency value over a sampling period. This samplingperiod may be, for example, the same sampling period defined for thecalculation of the average daily dispensing frequency values used todetermine which prescription items qualify for automatic stock trackingand replenishment, as discussed above with reference to FIG. 4A. Forexample, a user may select a grid cell within grid 415, select the checkbox in interactive cell options field 422 specifying the average day,and then specify this day as 3 average days in the appropriate field. Insuch a case, the minimum stocked number would be three times thecalculated average daily dispensing frequency value for prescriptionitems falling within the selected grid cell.

To provide an illustrative example, a user may select grid cell 415.3and select only the “max daily” option from interactive cell optionsfield 422, specifying the number of occurrences as 2. Although not shownin FIG. 4B for purposes of brevity, a tolerance number may also bespecified by a user, for example. Alternatively, a default tolerance maybe used (e.g., 10%). As discussed above with reference to FIG. 2, themaximum daily dispensing frequency value may be calculated by taking theaverage of the 2 top daily dispensing frequency values within 10% of oneanother over the sampling period. This advantageously filters out anyoutliers from the calculation of the maximum daily dispensing frequencyvalue, providing a more accurate count to use as the minimum stockednumber.

To provide another illustrative example, a user may select grid cell415.4 and, in addition to selecting the “max daily” option describeddirectly above, select the “average day” option from interactive celloptions field 422 and specify the average number of days as 3. In thiscase, the calculated minimum stocked number would be calculated as thegreater of 3 times the calculated average daily dispensing frequencyvalue or the maximum daily dispensing frequency value for the 2 topoccurrences within 10 percent of one another for prescription itemsfalling within grid cell 415.4.

To provide yet another illustrative example, a user may select grid cell415.5 and, in addition to selecting the “average day” option frominteractive cell options field 422, may also select the “max daily aver.of top x occurrences” option and specify the number of occurrences as10. As discussed above with reference to FIG. 2, the maximum averagedaily dispensing frequency value may be calculated by averaging the top10 highest daily dispensing frequency values within the sampling period(e.g., summing these values and dividing by 10). In this case, theminimum stocked number would be calculated as the greater of 3 times thecalculated average daily dispensing frequency value or the maximumaverage daily dispensing frequency value calculated from the top 10occurrences within the sampling period.

A user may repeat this process to assign cell options to each grid cellwithin grid 415. In this way, a complete rule may be established for anentire pharmacy's stock regarding a minimum stocked number that triggersthe generation and/or transmission of a purchase order for qualifyingprescription items associated with the ranges of each grid cellspecified in grid 415. The user interface may then be further utilizedto specify, for prescription items that qualify for automatic stocktracking, ordering, and replenishment, additional rule parameters tospecify the maximum stock number to keep on hand. This is furtherdiscussed below with reference to FIG. 4C.

Again, the range of costs used to qualify various prescribed items maybe any suitable unit such as single dosages, packs, bottles, etc. As aresult, embodiments include the calculated maximum number of aprescribed item facilitating an optimum amount of a prescribed itemregardless of how that particular item is dispensed. For example, thecost used on the grid may represent the cost per dispensing unit (e.g.,per tablet, per milliliter, per inhaler, etc.) as opposed to the cost ofprepackaged prescription items (e.g., per pack or per bottle).Therefore, embodiments include the stock replenishment processcalculating and ordering a number of equivalent prepackaged prescriptionitems such that, when delivered, the total number of stockedprescription items per dispensing unit will reach the specifiedcalculated maximum. For example, the minimum and maximum values may beexpressed in terms of a number of dispensing units (tablets, caplets,etc.), but when re-ordered, the purchase order may include a quantityexpressed in packs, each pack having multiple dispensing units.

FIG. 4C illustrates an exemplary user interface screen 440 to facilitatethe calculation of a maximum stocked number for a qualifyingprescription item in accordance with an exemplary embodiment of thepresent disclosure. In an embodiment, exemplary user interface screen440 corresponds to a transition from exemplary user interface screen400, 440, or 460 due to a user selecting tab 406 while in the otherexemplary user interface screen. As discussed above, exemplary userinterface 440 shares several portions with other exemplary userinterfaces. For example, grid association interactive button 409, gridcode field 410, grid structure interactive button 411, grid nameinteractive field 412, number of stores field 414, interactive commentsfield 416, interactive grid description field 418, and update commentsfield 419 are also displayed in exemplary user interface 440. Theseportions may perform the same functions as discussed above withreference to FIGS. 4A and 4B.

However, exemplary user interface 440 also includes an interactive celloptions field 442, which a user may utilize to set the various ruleparameters for each prescription item in grid 415 that qualifies forautomatic stock tracking and replenishment. For example, interactivecell options field 424 provides a user with the option to select one ofthe grid cells within grid 415 and to identify that grid cell as havinga number of days of average stock cover or no stock cover. In anembodiment, grid cells that do not qualify for automatic stock tracking,ordering, and replenishment may be set to “no stock cover” by default.Upon selecting the average days of stock cover option, a user mayspecify a number of days and select the interactive “ok” button 444 toapply these selections to an individual grid cell. Alternatively, a usermay select the interactive “cancel” button to 446 such that no changesare made to grid 415.

To provide an illustrative example, a user may select grid cell 415.4and specify the number of days of stock cover as 2. The maximum stockednumber may be calculated based upon a multiple (in this case a multipleof 2) of the average daily dispensing frequency value, which may be thesame average daily dispensing frequency value that is used in thecalculation of the minimum stocked number. The maximum stocked numbermay then be calculated using Eqn. 1 above, as previously discussed withreference to FIG. 2.

A user may repeat this process to assign cell options to each grid cellwithin grid 415. In this way, a complete rule set is established for anentire pharmacy's stock regarding a maximum stocked number ofprescription item stock to maintain for qualifying prescription itemsassociated with the ranges of each grid cell specified in FIG. 4A. Theuser interface may then be further utilized to specify, for prescriptionitems that qualify for automatic stock tracking, ordering, andreplenishment, additional parameters to specify exceptions to thevarious rules as discussed herein with respect to FIGS. 4A-4C. This isfurther discussed below with reference to FIG. 4D.

FIG. 4D illustrates an exemplary user interface screen 460 to facilitatethe calculation of one or more rule exceptions to apply to one or morequalifying prescription items in accordance with an exemplary embodimentof the present disclosure. In an embodiment, exemplary user interfacescreen 460 corresponds to a transition from exemplary user interfacescreen 400, 420, or 440 due to a user selecting tab 408 while in theother exemplary user interface screen. As discussed above, exemplaryuser interface 460 shares several portions with other exemplary userinterfaces. For example, grid association interactive button 409, gridcode field 410, grid structure interactive button 411, grid nameinteractive field 412, number of stores field 414, interactive commentsfield 416, interactive grid description field 418, and update commentsfield 419 are also displayed in exemplary user interface 440. Theseportions may perform the same functions as discussed above withreference to FIGS. 4A-C.

However, exemplary user interface 460 also includes an interactive celloptions field 462, which a user may utilize to set the various exceptionparameters for each prescription item in grid 415 that qualifies forautomatic stock tracking and replenishment. For example, interactivecell options field 462 provides a user with the option to select a“trade adjustment factor” (TAF) uplift to one or more of the grid cellswithin grid 415. In an embodiment, grid cells that do not qualify forautomatic stock tracking, ordering, and replenishment may be set to “noTAF uplift” by default. Upon selecting the TAF uplift option, a user mayselect the “apply” button to apply these selections to an individualgrid cell.

To provide an illustrative example, a user may select grid cell 415.4and apply a TAF uplift, which may be a default value or otherwisespecified by a user as desired. Although not illustrated in FIG. 4D forpurposes of brevity, the TAF uplift may be associated with auser-specified period of time, a default period of time, specificpharmacies or stores, specific groups of pharmacies or stores, specificcountries, regions, etc. The TAF uplift may function as an override, toincrease or decrease the calculated minimum and/or maximum stockednumbers of prescription items for short durations throughout the yearthat provide inaccurate, erratic, or unpredictable transactional data.The TAF uplift may additionally or alternatively allow the calculatedminimum and/or maximum stocked numbers of prescription items to becalculated using prescribed item transaction data from a large group ofstores or pharmacies, but allow for adjustments to be applied as anotherlayer of rules to subsets of those stores. In this way, the TAF mayprovide additional convenience and customization when managing stock fora large number of pharmacies that may span several regions, states,countries, etc.

Although interactive cell options field 462 is shown in FIG. 4D ashaving only two selectable options, embodiments include interactive celloptions field 462 having any suitable number of options to facilitatethe entry and application of various rule exception parameters. Forexample, calculated minimum and maximum stocked numbers may be increasedor decreased for particular grid cells, over specific dates, and/or forspecific stores. To provide another example, the qualifying ranges ofaverage daily dispensing frequency values and/or cost ranges may beadjusted over specific dates and/or for specific stores, etc.

FIG. 5 illustrates an exemplary method 500 in accordance with anexemplary embodiment of the present disclosure. In an embodiment, method500 may be implemented by any suitable device, such as one or moreexternal computing devices 114.1-114.N and/or one or more pharmacycomputing devices, such as computing devices 104.1-104.M, for example,as shown in FIG. 1. In an embodiment, method 500 may be performed by anysuitable combination of one or more processors, applications,algorithms, and/or routines, such as any processor 202 executinginstructions stored in memory 210 in conjunction with data received viacommunication unit 204, for example.

Method 500 may start when one or more processors receive a samplingperiod over which to analyze a dispensing frequency of a prescriptionitem (block 502). This may include, for example, a user providing thesampling period via a suitable user interface (e.g., one associated witha pharmacy computing device, such as one or more computing devices104.1-104.M, as shown in FIG. 1) and communicating this sampling periodto another external computing device (e.g., one or more externalcomputing devices 114.1-114.N, as shown in FIG. 1) (block 502). This mayalso include, for example, an application installed on an externalcomputing device providing a default sampling period (block 502). Again,the sampling period may be any suitable sampling period, such as 30days, 6 months, 1 year, etc.

Method 500 may include one or more processors calculating an averagedaily dispensing frequency value for the prescription item over thesampling period (block 504). For example, for a 30 day sampling period,a specific prescription drug may be dispensed a total of 300 times. Insuch a case, the average daily dispensing frequency value for thatprescription item would be 10 prescription items dispensed per day.

Method 500 may include one or more processors determining whether theaverage daily dispensing frequency value for the prescription item(block 504) is within a specified range of frequency values (i.e.,ranging frequency) (block 506). This may include, for example, adetermination of whether a particular prescribed item is dispensed at anaverage daily dispensing frequency that falls with a range of averagedaily dispensing frequency values specified by a user (block 506). Forexample, a user may provide the range of average daily dispensingfrequency values in accordance with the creation of a number of gridcells, as discussed above with reference to FIG. 4A. If the averagedaily dispensing frequency value for the prescription item falls withinthe specified range of average daily dispensing frequency values, theprescription item potentially qualifies for automated stock tracking,ordering, and replenishment, and method 500 may continue to determinewhether the cost of the prescription item is also within a range ofcosts to verify this (block 508). Otherwise, the prescription item doesnot qualify for automatic prescription stock tracking, ordering, andreplenishment (block 510).

Method 500 may include one or more processors determining whether thecost of the prescription item is within a specified range of costs(block 508). This may include, for example, a determination of whether aprescription item that potentially qualifies for automated stocktracking, ordering, and replenishment (block 506) actually qualifies dueto the cost of the potentially qualifying prescription item having acost that falls with a range of costs specified by a user (block 508).For example, a user may provide the range of costs in accordance withthe creation of a number of grid cells, which intersect with thespecified range of average daily dispensing frequency values asdiscussed above with reference to FIG. 4A. If the cost of theprescription item falls within the specified range of costs, then method500 may continue such that the prescription item qualifies for automatedstock tracking, ordering, and replenishment (block 512). Otherwise, theprescription item does not qualify for automatic stock tracking,ordering, and replenishment (block 510).

Method 500 may include one or more processors tracking a prescriptionitem that qualifies for automatic stock tracking, ordering, andreplenishment (block 512). This may include, for example, monitoringstock files from a pharmacy associated with the prescription item toensure that purchase orders are generated and transmitted upon thestocked number of the tracked prescription item falling below aspecified minimum stocked number, which is discussed further below withreference to FIG. 6 (block 512). This tracking may occur over anysuitable sampling period, such as continuously, each day, each time astock file is updated, at the close of business of each pharmacy, etc.(block 512).

FIG. 6 illustrates an exemplary method 600 in accordance with anexemplary embodiment of the present disclosure. In an embodiment, method600 may be implemented by any suitable device, such as one or moreexternal computing devices 114.1-114.N, for example, as shown in FIG. 1.In an embodiment, method 600 may be performed by any suitablecombination of one or more processors, applications, algorithms, and/orroutines, such as any processor 202 executing instructions stored inmemory 210 in conjunction with data received via communication unit 204,for example. In an embodiment, method 600 may be applied to one or moreprescribed items that qualify for automatic stock tracking, ordering,and replenishment, as discussed above with reference to FIG. 5 (block512).

Method 600 may start when one or more processors calculate a minimumstocked number for a qualifying prescription item (block 602). This mayinclude, for example, a user specifying any suitable combination ofmetrics derived from the prescribed item's transaction history over thesampling period, as discussed above with reference to FIG. 4B (block604).

Method 600 may include one or more processors calculating a maximumstocked number for the qualifying prescription item (block 604). Thismay include, for example, a user specifying any suitable combination ofmetrics derived from the prescribed item's transaction history over thesampling period, as discussed above with reference to FIG. 4C (block604).

Method 600 may include one or more processors monitoring inventorylevels associated with the qualifying prescription item (block 606).Again, the monitoring may be performed over any suitable samplingperiod, such as continuously, each day, each time a stock file isupdated, at the close of business of each pharmacy, etc. (block 606).

Method 600 may include one or more processors determining whether astocked number of a qualifying prescription item has fallen below theminimum stocked number (block 602) to potentially require a purchaseorder being generated (block 608). If so, method 600 may continue todetermine whether any exceptions or other factors exist for theparticular prescription item (block 610). Otherwise, method 600 mayrevert to continuing to monitor inventory levels (block 606).

Method 600 may include one or more processors determining whether aprescription item, once its stock number has been depleted to less thanthe minimum stocked number (block 602) is subject to a stock trackingexception that obviates the purchase order submission (block 610). Thismay include, for example, one or more TAF uplifts that may apply to theparticular prescription item and/or other exceptions that may be basedupon dates, regions, specific stores, etc., as discussed above withreference to FIG. 4D (block 610). If one or more stock trackingexceptions do exist, method 600 may revert to continuing to monitorinventory levels (block 606). Otherwise, method 600 may continue suchthat a purchase order is generated and submitted to replenish thedepleted stock of the prescription item (block 612).

Method 600 may include one or more processors submitting a purchaseorder to replenish stock of the prescription item (block 612). In someembodiments, the purchase order may be for an amount of the prescribeditem such that, upon the order being fulfilled, the prescription itemstock is equal to or less than the maximum (block 604) stocked number(block 612). The purchase order submission may include any suitablemanual, automated, or semi-automated process that generates, transmits,or otherwise results in the stock of the prescription item beingreplenished, as discussed above, for example, with reference to FIG. 1(block 612). Upon submission of a purchase order to replenish stock,method 600 may continue to monitor inventory levels (block 606), andrepeat the process of monitoring, ordering, and replenishing stock asprescription items are dispensed.

As discussed above, embodiments are described to facilitate whether aprescription item qualifies for automatic stock tracking, thecalculation of a minimum stocked number, the calculation of a maximumstocked number, the calculation of one or more rule exceptions to applyto one or more qualifying prescription items, etc. As discussed above, auser may specify user-defined parameters that are used in conjunction inthe aforementioned calculations and determinations.

For example, a user may manually specify or select predetermined ordefault minimum and maximum stocked numbers of prescription items aspart of the tracking and replenishment process instead of having thesenumbers calculated from stock item transaction data. To provide anotherexample, a user may manually specify or select from variouspredetermined or default options such as a suitable sampling time periodfor which prescription item transaction data may be analyzed, which maydiffer for different prescription products and/or different pharmacylocations.

To provide additional examples, as discussed with reference to FIG. 4B,a tolerance number may also be specified by a user or a defaulttolerance may be used as part of the calculation of the maximum dailydispensing frequency value. To provide yet another example, as discussedwith reference to FIG. 4D, the TAF uplift may be a default value orotherwise specified by a user.

Although not shown for purposes of brevity, embodiments include asuitable computing device (e.g., external computing device 114.N, asshown in FIG. 1) being configured to display an interactive productparameter screen, with which a user (e.g., user 115) may interact tospecify these types of product parameters, among others. In variousembodiments, the interactive product parameter screen may include anysuitable user interface to allow a user to enter any suitable numberand/or type of parameters that may be used as part of the rule sets tofacilitate prescription item stock tracking, ordering, andreplenishment. For example, upon a user specifying minimum and maximumstocked numbers of prescription items, a sampling time period for whichprescription item transaction data may be analyzed, a tolerance number,a TAF uplift value, etc., the computing device may store these values asdata in a suitable portion of central hosting service 114 such that thedata may be accessed to implement execution of the stock managementapplication and the various embodiments described herein.

As used herein, the term “pharmacy” may include, for example, a singleoutlet or a plurality of outlets affiliated with one or more entitiesthat are licensed to dispense prescribed pharmaceutical products such asdrugs, medicaments, durable medical equipment, etc. The one or moreentities may be located, for example, in geographic locations separatefrom one another, in different areas of the same city, or in differentstates, countries, etc. The pharmacy outlets may include, for example,one or more of a conventional retail store, space within a locationoperated by another commercial or not-for-profit entity (e.g., within adiscount store, hospital, school, nursing home, etc.), an outlet inproximity with a warehouse or distribution center, a call-in pharmacy, along-term care pharmacy, a workplace/on-site pharmacy, a specialtypharmacy, etc. The pharmacy may be commercial or not-for-profit, and mayprovide or vend other products in addition to the prescribedpharmaceutical products.

As used herein, the term “pharmacy computing system” may include acomputing system that is owned and/or operated by a pharmacy to aidpharmacy employees and representatives to fill and dispense prescribedpharmaceutical products and other products. A pharmacy computing systemmay include at least one computing device, database, display device, anduser input interface device. Typically, each outlet of a pharmacy mayhave a local instance of (or local access to) a pharmacy computingsystem. In some embodiments, local instances of a pharmacy computingsystem may be networked.

Although the foregoing text sets forth a detailed description ofnumerous different embodiments, it should be understood that thedetailed description is to be construed as exemplary only and does notdescribe every possible embodiment because describing every possibleembodiment would be impractical, if not impossible. In light of theforegoing text, one of ordinary skill in the art will recognize thatnumerous alternative embodiments could be implemented, using eithercurrent technology or technology developed after the filing date of thispatent application.

What is claimed is:
 1. A method of performing prescription stockmanagement, comprising: identifying, by one or more processors, one ormore qualifying prescription items from a plurality of prescriptionitems, each qualifying prescription item being dispensed over a samplingperiod at an average daily dispensing frequency value; calculating, byone or more processors, for a qualifying prescription item from amongthe qualifying prescription items, a maximum stocked number;calculating, by one or more processors, for the qualifying prescriptionitem from among the qualifying prescription items, a minimum stockednumber based upon forecasting future demand for the qualifyingprescription item; transmitting, by one or more processors, an order toan external computing device when a stocked number of the qualifyingprescription item is less than the minimum stocked number, and whereinthe order, upon being fulfilled, results in a replenishment of thequalifying prescription item such that the stocked number of thequalifying prescription item is greater than the minimum stocked numberand up to the maximum stocked number.
 2. The method of claim 1, whereinforecasting future demand for the qualifying prescription item furthercomprises forecasting future demand based on applying variousstatistical analyses to transactions of the qualifying prescriptionitem.
 3. The method of claim 1, wherein forecasting future demand forthe qualifying prescription item further comprises forecasting futuredemand based on recent changes in the dispensation rate of thequalifying prescription item.
 4. The method of claim 1, furthercomprising: calculating, by one or more processors, a multiple of theaverage daily dispensing frequency value of the qualifying prescriptionitem; and calculating, by one or more processors, the maximum stockednumber as a sum of (i) the minimum stocked number of the qualifyingprescription item, and (ii) the multiple of the average daily dispensingfrequency value of the qualifying prescription item.
 5. The method ofclaim 1 wherein forecasting future demand for the qualifyingprescription item further comprises calculating, by one or moreprocessors, a multiple of average daily dispensing frequency value ofthe qualifying prescription item over the sampling period.
 6. The methodof claim 1 wherein forecasting future demand for the qualifyingprescription item further comprises: receiving, by one or moreprocessors, a number of days associated with highest daily dispensingfrequency values within the sampling period for the qualifyingprescription item; and calculating, by one or more processors, a maximumaverage daily dispensing frequency value by averaging each of thehighest daily frequency dispensing values over the number of days. 7.The method of claim 1, wherein forecasting future demand for thequalifying prescription item further comprises: receiving, by one ormore processors, a number of daily dispensing frequency values withinthe sampling period for the qualifying prescription item, the number ofdaily dispensing frequency values corresponding to a top number ofoccurrences over the sampling period within a threshold variance; andcalculating, by one or more processors, a maximum daily dispensingfrequency value by averaging a sum of the daily dispensing frequencyvalues over their number of occurrences within the sampling period.
 8. Acomputing device that facilitates prescription stock management,comprising: a communication unit configured to receive a history ofprescribed prescription item transactions; a memory configured to storethe history of prescribed prescription item transactions; and aprocessor configured to: identify one or more qualifying prescriptionitems from a plurality of prescription items, each qualifyingprescription item being dispensed over a sampling period at an averagedaily dispensing frequency value, calculate for a qualifyingprescription item from among the qualifying prescription items, amaximum stocked number, and calculate for the qualifying prescriptionitem from among the qualifying prescription items, a minimum stockednumber based upon forecasting future demand for the qualifyingprescription item, wherein the communication unit is further configuredto transmit an order to an external computing device when a stockednumber of the qualifying prescription item is less than the minimumstocked number, and wherein the order, upon being fulfilled, results ina replenishment of the qualifying prescription item such that thestocked number of the qualifying prescription item is greater than theminimum stocked number and up to the maximum stocked number.
 9. Thecomputing device of claim 8, wherein the processor is further configuredto forecast future demand for the qualifying prescription item based onapplying various statistical analyses to transactions of the qualifyingprescription item.
 10. The computing device of claim 8, wherein theprocessor is further configured to forecast future demand for thequalifying prescription item based on recent changes in the dispensationrate of the qualifying prescription item.
 11. The computing device ofclaim 8, wherein the processor is further configured to: calculate amultiple of the average daily dispensing frequency value of thequalifying prescription item; and calculate the maximum stocked numberas a sum of (i) the minimum stocked number of the qualifyingprescription item, and (ii) the multiple of the average daily dispensingfrequency value of the qualifying prescription item.
 12. The computingdevice of claim 8, wherein the processor is further configured tocalculate a multiple of average daily dispensing frequency value of thequalifying prescription item over the sampling period.
 13. The computingdevice of claim 8, wherein the processor is further configured to:receive a number of days associated with highest daily dispensingfrequency values within the sampling period for the qualifyingprescription item; and calculate a maximum average daily dispensingfrequency value by averaging each of the highest daily frequencydispensing values over the number of days.
 14. The computing device ofclaim 8, wherein the processor is further configured to: receive anumber of daily dispensing frequency values within the sampling periodfor the qualifying prescription item, the number of daily dispensingfrequency values corresponding to a top number of occurrences over thesampling period within a threshold variance; and calculate a maximumdaily dispensing frequency value by averaging a sum of the dailydispensing frequency values over their number of occurrences within thesampling period.
 15. A non-transitory, tangible computer-readable mediumstoring machine readable instructions that, when executed by aprocessor, cause the processor to: identify one or more qualifyingprescription items from a plurality of prescription items, eachqualifying prescription item being dispensed over a sampling period atan average daily dispensing frequency value; calculate for a qualifyingprescription item from among the qualifying prescription items, amaximum stocked number; calculate for the qualifying prescription itemfrom among the qualifying prescription items, a minimum stocked numberbased upon forecasting future demand for the qualifying prescriptionitem; and transmit an order to an external computing device when astocked number of the qualifying prescription item is less than theminimum stocked number, wherein the order, upon being fulfilled, resultsin a replenishment of the qualifying prescription item such that thestocked number of the qualifying prescription item is greater than theminimum stocked number and up to the maximum stocked number.
 16. Thenon-transitory, tangible computer-readable medium of claim 15, furtherincluding instructions that, when executed by the processor, cause theprocessor to forecast future demand for the qualifying prescription itembased on applying various statistical analyses to transactions of thequalifying prescription item.
 17. The non-transitory, tangiblecomputer-readable medium of claim 15, further including instructionsthat, when executed by the processor, cause the processor to forecastfuture demand for the qualifying prescription item based on recentchanges in the dispensation rate of the qualifying prescription item.18. The non-transitory, tangible computer-readable medium of claim 15,further including instructions that, when executed by the processor,cause the processor to: calculate a multiple of the average dailydispensing frequency value of the qualifying prescription item; andcalculate the maximum stocked number as a sum of (i) the minimum stockednumber of the qualifying prescription item, and (ii) the multiple of theaverage daily dispensing frequency value of the qualifying prescriptionitem.
 19. The non-transitory, tangible computer-readable medium of claim15, further including instructions that, when executed by the processor,cause the processor to calculate a multiple of average daily dispensingfrequency value of the qualifying prescription item over the samplingperiod.
 20. The non-transitory, tangible computer-readable medium ofclaim 15, further including instructions that, when executed by theprocessor, cause the processor to: receive a number of days associatedwith highest daily dispensing frequency values within the samplingperiod for the qualifying prescription item; and calculate a maximumaverage daily dispensing frequency value by averaging each of thehighest daily frequency dispensing values over the number of days.